Cognitive Radio Networks: Performance, Applications and Technology


Chee Wei Tan (Editor)
City University of Hong Kong, Kowloon Tong, Hong Kong, China

Series: Electronics and Telecommunications Research
BISAC: TEC041000

Over the past two decades, there have been rapid and significant developments in the field of wireless networking, especially with the emergence of wireless cognitive radio network technologies. There are, however, fundamental limits to communications and radio resource is scarce in the face of demand. This gives rise to new challenges in jointly managing resource allocation and interference management in a cognitive manner. The first cognitive radio wireless standard, IEEE 802.22, was only published in 2011, whereby white space – referring to the unused frequency spectrums that are location-specific – in television channels can be identified for use by other devices in a cognitive radio network.

Recently, the U.S. Defense Advanced Research Projects Agency has also recognized the importance of wireless cognitive radio network technologies in military and civilian applications, and organized the 2017 DARPA Spectrum Collaboration Challenge to spur new ideas and experimentation to overcome spectrum scarcity. The need to cognitively access the increasingly-crowded electromagnetic spectrum has never been greater. This book, written by a team of leading experts, aims at providing the readers with a series of tutorials on a variety of cognitive radio network technologies ranging from efficient dynamic spectrum sharing and interference management to optimal resource allocation and to fundamental limits in communications. Emphasis is on cutting edge research in theoretical tools, algorithms and engineering insights to provide guiding principles, making this an ideal reference book.

Table of Contents

Table of Contents


Chapter 1. A Tutorial on Multichannel Rendezvous in Cognitive Radio Networks
(Cheng-Shang Chang, Duan-Shin Lee, and Wanjiun Liao, Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan, R.O.C.)

Chapter 2. Joint Energy-Bandwidth Allocation for Multiple Broadcast Channels with Energy Harvesting
(Vaneet Aggarwal, Xiaodong Wang, and Zhe Wang, Purdue University, West Lafayette, NJ, and Columbia University, New York, NY, USA)

Chapter 3. Opportunistic Spatial Sharing for LTE and WiFi Co-Existence in the Unlicensed Spectrum
(Cong Shen, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China)

Chapter 4. Reinforcement Learning Based PHY-Layer Authentication in Cognitive Radio Networks
(Liang Xiao, School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China)

Chapter 5. Max-Min Utility Fair Power Control in Cognitive Radio Networks
(Y.-W. Peter Hong, Liang Zheng, and Chee Wei Tan, Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan, and Princeton University, NJ, USA)

Chapter 6. Beamforming Duality and Algorithms for Weighted Sum Rate Maximization in Cognitive Radio Networks
(I-Wei Lai, Liang Zheng, Chee Wei Tan, and Chia-Han Lee, Department of Electrical Engineering, National Taiwan Normal University, Taipei, Taiwan)

Chapter 7. Energy Minimization by Power Control in Heterogeneous Cognitive Radio Networks
(Xiangping Zhai, Chee Wei Tan, and Bhaskar D.Rao, Nanjing University of Aeronautics and Astronautics, City University of Hong Kong, Hong Kong, China, and University of California, San Diego, CA, USA)

Chapter 8. Cognitive Radio Networks: An Information-Theoretic Perspective
(Mojtaba Vaezi, Princeton University, Princeton, NJ, USA)

Chapter 9. On the Role of Channel Side Information in Cognitive Radios
(Stefano Rini, National Chiao Tung University, Hsinchu, Taiwan, R.O.C.)

Chapter 10. On Security of Cognitive Radio Networks: An Information Theoretic Model with Wiretap Channels
(Congduan Li, City University of Hong Kong, Hong Kong, China)


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